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than that for a single asset class benchmark.
Many single asset classes have a known universe of securities
or investment options that constitute “the market”
and can be used to establish a nearly definitive single asset
class benchmark. Other single asset classes, such as commodities,
do not have such a defined market, so reasonable
proxies are established and marketed with one or two
emerging as the standard.
In either case, any single asset class benchmark is designed
to identify the aggregate performance of the class and allow
for standardized comparisons between and among market
participants and managers within that class. Advisers can
then measure the implementation skill, or “alpha,” behind a
specific investment assignment.
However, a multi-asset class benchmark is generally
designed to measure something else—the total alpha of all
such investment assignments plus the alpha, if any, of a policy
portfolio itself.
What is a policy portfolio in a multi-asset class context?
It is the mix of asset classes and weights derived from the
set of short- and long-term investment objectives and capital
market assumptions for an investor or investment plan. This
mix may change over time in certain ways to reflect changing
objectives (e.g., liabilities) or assumptions (an attempt
to capture excess returns from short-term asset class price
fluctuations in (market timing). 2
Establishing a policy portfolio is not an easy task. Numerous
challenges and complexities arise almost immediately.
• How are these decisions made in practice?
• How are specific asset classes included?
• How are the weights set?
• Where do the capital market assumptions come from?
• How do these decisions evolve over time?
For example, multi-asset class efficient frontiers are
based on, and highly sensitive to, their inputs and may
contain volatile or inaccurate data (private equity and
venture capital performance data come to mind), making
it difficult to gain agreement on what that efficient frontier
looks like. This is further complicated by the fact that
there is no standing consensus on the asset-class palette;
after all, the simple decision to invest strictly in domestic
equities (or any other set of asset classes) creates the
opportunity cost of not investing in some other market,
such as international equities, commodities, real estate or
bonds, to name just a few.
Establishing a policy portfolio is not a trivial exercise either.
Analysis shows that the asset allocation decision explains
about 90 percent of the variability of a fund’s returns over
time, and on average across funds, explains approximately 100
percent of the level of returns. 3 The constraints and decisions
that drive the policy portfolio, whatever they may be, clearly
have a big impact and must be evaluated appropriately.
Of course, an investor (and their adviser or consultant)
must construct a policy portfolio even in the absence of
specific guidance on these matters. After all, establishing
an investment policy, delineating responsibility and measuring
the performance contribution of those activities
form the core of the investment management process. 2
Yet benchmark identification is routinely dismissed as a
lesser element of the process; since there is no single definitive
approach, the ultimate decision is viewed as relatively
inconsequential.
This perception is far from accurate. The need for benchmarking
is heightened, not diminished, in a multi-asset class
environment given the much wider spectrum of required
decision making and investment opportunities.
The Case Of Target Date
In recent years, the individual retirement market has
witnessed an explosion of “target date” products. These are
multi-asset class products that dynamically and automatically
evolve an investor’s “policy portfolio”—their asset class mix
and weights—at each stage of an investor’s working life.
The benchmark process in this realm is very challenging.
How should such evolving policy portfolios be measured
against the finite horizons of individual investors
who have real-world and often conflicting needs that may
vary with age, existing wealth, living expenses and personal
circumstances?
Given existing tools and capabilities, there may be a reasonable
approach to benchmarking. In general, the proper
design of a portfolio involves at least four decisions 2 : (1) the
asset-class palette; (2) strategic asset allocations; (3) tactical
asset allocations (market timing); and (4) security selection.
The first two decisions form the core of the policy portfolio,
and should be the focus of benchmarking in a multi-asset
class environment.
Ultimately, though, there will be ongoing debate about
the objective nature and best practices of benchmarking
such multi-asset class portfolios. The different approaches
will each bring their own strengths and weakness, but the
growing competition can only help benefit the market drive
toward the optimal approach.
Jeffrey Fernandez, project manager, Analytics & Research,
Dow Jones Indexes, contributed to this article.
References
1 Bailey, Jeffery V., “Are Manager Universes Acceptable Performance Benchmarks?” Journal of Performance Management, Spring 1992.
2 Brinson, Gary P., L. Randolph Hood, and Gilbert L. Beebower, “Determinants of Portfolio Performance,” Financial Analysts Journal, July/August 1986.
http://www.cfapubs.org/doi/pdfplus/10.2469/faj.v51.n1.1869
3 Ibbotson, Roger G. and Paul D. Kaplan, “Does Asset Allocation Policy Explain 40, 90, or 100 Percent of Performance?” Financial Analysts Journal, January/February 2000.
http://corporate.morningstar.com/ib/documents/MethodologyDocuments/IBBAssociates/AssetAllocationExplain.pdf
www.journalofindexes.com July/August 2009
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